Master the First Principles of Robotics

Name: Master the First Principles of Robotics
Price: 12.75 USD
Availability: InStock

10h 16s

English

Paid

June 6, 2026

Master the First Principles of Robotics is a 67-lesson 10 hours self-paced course by Elliot Lee, UBICODERS. Learn robotics from the ground up.

Course facts

Lessons: 67
Duration: 10 hours
Level: All levels
Language: English
Updated
Instructor: Elliot Lee, UBICODERS
Price: Premium

Learn robotics from the ground up. In this course, you will build a drone and a small ground robot. You will base each step on clear first principles like control theory, system dynamics, and sensor fusion. You will not rely on ROS or hidden tools. You will think and work like an engineer.

How You Will Learn

You will follow a tight loop of Math → Code → Reality. You start with simple math and physics models. You turn these models into code. You test the code on virtual robots that face noise and other real‑world limits.

What You Will Build

You will write your own drivers, controllers, and state estimators. You will build filters and fuse sensor data. You will learn how each part works, not just how to call a library.

Why This Approach Matters

This course shifts you from an integrator to an engineer. You will learn how a robot reads the world through sensors. You will see how math shapes the model of that world. You will link these models to control and motion planning.

Who This Course Is For

This course is for learners who want more than step‑by‑step guides. It suits you if you want to design and build full robotic systems on your own.

Who teaches Master the First Principles of Robotics?

Elliot Lee

Hongyun “Elliot” Lee — a robotics engineer and founder of several small projects in the field of autonomous systems and robotics education. He is best known as the creator of the Ubicoders platform.

Key Facts

Full name: Hongyun (Elliot) Lee
Profession: aerospace / robotics software engineer
Founder of the company AIR&H Aerospace Inc.
Founder of the educational platform Ubicoders
Location: Richmond, British Columbia, Canada

UBICODERS

Ubicoders is a small educational platform focusing on robotics, autonomous systems, and computer vision. The main idea is to teach engineers to create robots and autonomous devices through mathematics, code, and simulations.

Course topics include:

robotics engineering
computer vision
machine learning
visual odometry
SLAM
ROS2
embedded systems
robot control (PID, control theory)

What lessons are included in Master the First Principles of Robotics?

0:00

#1: 001 Intro

All Course Lessons (67)

#	Lesson Title	Duration
1	001 Intro Demo	04:16
2	002 Backgrounds	02:01
3	003 Course Guide (Download The Code Here)	04:12
4	004 Which Code Environment	01:25
5	005 What is Conda (Optional)	01:21
6	006 What is Docker (Optional)	05:51
7	007 Easy Setup Windows Conda	05:07
8	008 Easy Setup Mac Conda	05:34
9	009 Standard Setup Ubuntu 22	05:42
10	010 Standard Setup - Windows WSL	11:30
11	011 Python Basics 1	15:50
12	012 Trig. Functions	03:45
13	013 Calculus	11:51
14	014 Taylor Series & Fourier Series	08:33
15	015 Linear Algebra	13:49
16	016 Differential Equation	09:30
17	017 Statistics (Mean and Variance)	08:49
18	018 Statistics (Gaussian Distribution)	06:49
19	019 Eigen Values and Vectors	08:45
20	020 Closure	01:17
21	021 Level Introduction	01:29
22	022 Virtual Robot Scripts	04:28
23	023 Realtime Graphing	02:38
24	024 Data Collection	04:54
25	025 Terminals in Virtual Robots	09:37
26	026 PID Control 1	11:50
27	027 PID Control 2	12:42
28	028 PID Control 3	17:22
29	029 PID Control 4 Cascade PI	07:31
30	030 States	09:36
31	031 Rotation Matrix 1	07:51
32	032 Rotation Matrix 2	06:35
33	033 Rotation Matrix 3	15:38
34	034 Inertial Sensors	04:35
35	035 Inertial Sensors Accelerometer	12:45
36	036 Inertial Sensors Magnetometer	06:13
37	037 Inertial Sensors Gyroscope 1	06:22
38	038 Inertial Sensors Gyroscope 2	13:02
39	039 Inertial Sensors Gyroscope 3	10:37
40	040 Noise Filtering	02:39
41	041 Noise Filtering Average Window	08:08
42	042 Noise Filtering Low-pass Filter	05:02
43	043 Introduction	11:49
44	044 Height (Altitude) Control 1	25:29
45	045 Height (Altitude) Control 2	02:43
46	046 Rate Control	14:52
47	047 Attitude Control	09:41
48	048 Velocity Control 1	14:09
49	049 Velocity Control 2	11:14
50	050 Capstone	07:56
51	051 DCM Introduction	04:15
52	052 DCM Preview 1	18:29
53	053 DCM Preview 2	11:52
54	054 DCM Theory	05:52
55	055 DCM Code	20:43
56	056 DCM Multirotor	19:44
57	057 State Space Introduction	10:20
58	058 State Space Control	06:18
59	059 State Space Multirotor 1	08:35
60	060 State Space Multirotor 2	08:20
61	061 Mass Spring Damper	16:28
62	062 Nonlinear System	10:36
63	063 Kalman Filter Introduction	06:11
64	064 Kalman Filter Code	15:53
65	065 Kalman Filter Theory	08:18
66	066 Extended Kalman Filter	10:25
67	067 Exit	02:33

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Frequently asked questions

What are the prerequisites for this course?

The course does not require prior knowledge in robotics, but familiarity with basic programming and mathematics will be beneficial. Lessons such as Python Basics, Trigonometric Functions, and Calculus are included to support foundational learning. Optional lessons on Conda and Docker are available for those unfamiliar with these environments.

What projects will I build during the course?

You will build two main projects: a drone and a small ground robot. These projects involve writing your own drivers, controllers, and state estimators, as well as building filters and fusing sensor data. The focus is on understanding how each component works rather than using pre-built libraries.

Who is the target audience for this course?

The course is designed for learners who seek a deeper understanding of robotics beyond step-by-step guides. It is ideal for those interested in designing and building complete robotic systems independently, using first principles and engineering methods.

What specific tools or platforms are used in the course?

While the course does not rely on ROS or hidden tools, it uses Python for coding and offers optional guidance on using Conda and Docker for environment setup. The course includes lessons on setting up environments on different operating systems like Windows, Mac, and Ubuntu.

What topics are not covered in this course?

The course does not cover the use of ROS (Robot Operating System) or other high-level robotics frameworks. The focus is on building understanding from the ground up using first principles rather than relying on existing libraries or tools.

How much time should I expect to commit to this course?

The course comprises 67 lessons, each building on the previous. While the exact time commitment will vary depending on your pace, the course involves a comprehensive learning loop of Math → Code → Reality, which requires diligent practice and application.

How can the skills learned in this course be applied to other areas or careers?

The skills acquired in this course, such as control theory, system dynamics, and sensor fusion, are fundamental in robotics and can be applied to various fields like autonomous vehicles, aerospace, and industrial automation. The engineering approach emphasized in the course prepares you for roles that require designing and implementing complex systems from the ground up.